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A Derivational Model of Discontinuous Parsing

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Language and Automata Theory and Applications (LATA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10168))

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Abstract

The notion of latent-variable probabilistic context-free derivation of syntactic structures is enhanced to allow heads and unrestricted discontinuities. The chosen formalization covers both constituent parsing and dependency parsing. The derivational model is accompanied by an equivalent probabilistic automaton model. By the new framework, one obtains a probability distribution over the space of all discontinuous parses. This lends itself to intrinsic evaluation in terms of perplexity, as shown in experiments.

The second author has been funded by the Academy of Finland (Academy Research Fellowship; decision no 270354).

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Authors and Affiliations

  1. School of Computer Science, University of St Andrews, St Andrews, UK

    Mark-Jan Nederhof

  2. Department of Modern Languages, University of Helsinki, Helsinki, Finland

    Anssi Yli-Jyrä

Authors
  1. Mark-Jan Nederhof
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  2. Anssi Yli-Jyrä
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Corresponding author

Correspondence to Mark-Jan Nederhof .

Editor information

Editors and Affiliations

  1. Umeå University, Umeå, Sweden

    Frank Drewes

  2. Rovira i Virgili University, Tarragona, Spain

    Carlos Martín-Vide

  3. University of Giessen, Giessen, Germany

    Bianca Truthe

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Nederhof, MJ., Yli-Jyrä, A. (2017). A Derivational Model of Discontinuous Parsing. In: Drewes, F., Martín-Vide, C., Truthe, B. (eds) Language and Automata Theory and Applications. LATA 2017. Lecture Notes in Computer Science(), vol 10168. Springer, Cham. https://doi.org/10.1007/978-3-319-53733-7_22

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  • DOI: https://doi.org/10.1007/978-3-319-53733-7_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53732-0

  • Online ISBN: 978-3-319-53733-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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